Innovative data sources offer new ways of studying spatial and temporal industrial and regional development. Our approach is to study the development of an entrepreneurial regional economy through a comprehensive analysis of its constituent firms and institutions over time.
We develop Granger causality tests that apply directly to data sampled at different frequencies. We show that taking advantage of mixed frequency data allows us to better recover causal relationships when compared to the conventional common low frequency approach.
We present a survey design that generalizes static conjoint experiments to elicit inter-temporal adoption decisions for durable goods. We show that consumers’ utility and discount functions in a dynamic discrete choice model are jointly identified using data generated by this specific design. In contrast, based on revealed preference data, the utility and discount functions are generally not jointly identified even if consumers’ expectations are known.
Inspired by a data set from the Chinese retailer JD.com, we study the click and purchase behavior of customers in an online retail setting by employing a structural estimation approach.
Hasbrouck (2018) takes advantage of the fact that U.S. equity market data are timestamped to nanosecond precision, and explores models of price dynamics at resolutions sufficient to capture the reactions of the fastest agents. The paper therefore addresses the econometric analysis of multivariate time series models at sub-millisecond frequencies and relies on long distributed lag models to alleviate the computational complexity while still taking advantage of the inherent sparsity of price transitions.
The autonomous car began as an opportunity that required breaking all kinds of limits: engineering, navigation, adjusting to traffic conditions, distinguishing objects, predicting what those objects might do, reacting in time, calculating quickly and juggling a vast number of ever-changing variables. The developers used more and more computer power to address these needs. But the initial bounding limit turned out to be very fundamental; rule-based computers don’t have pattern power.
The COVID-19 pandemic has generated a significant shift in how and where we work, play and live. In this Kenan Insight, we explore which changes will be temporary and which are here to stay.
Although store brands (SBs) are becoming increasingly important across the world, their success varies dramatically across consumer packaged goods categories and countries. The purpose of this paper is to provide insight into how such differences in SB success originate.
The emerging theory-based view depicts entrepreneurs as sophisticated thinkers who form, update, and act on rich causal theories. In support of this view, recent empirical work has demonstrated both (a) the value of theories as well as (b) the importance of experimentation for testing and refining theories. Yet, the process by which entrepreneurs initially form these theories remains largely unobserved.
We study the role of information in asset pricing models with long-run cash flow risk. When investors can distinguish short- from long-run consumption risks (full information), the model generates a sizable equity risk premium only if the equity term structure slopes up, contrary to the data.
How will the hurricanes affect economic data for October? Kenan Institute Research Fellow Greg Brown will look at the data during the institute’s monthly virtual briefing at 9 AM EDT Friday, November 1.
Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. Rising automation is happening in a period of growing economic inequality, raising fears of mass technological unemployment and a renewed call for policy efforts to address the consequences of technological change. In this paper we discuss the barriers that inhibit scientists from measuring the effects of AI and automation on the future of work.
As the historic 2020 U.S. presidential election draws nearer, voters are taking stock of the impact the COVID-19 pandemic has had on their lives and livelihoods, and demanding that policymakers present their plans for economic recovery. In this Kenan Insight, we look at the major forces reshaping the U.S. economy and offer suggestions for forging an intentional and equitable path forward.
The argument that ESG investing generates more stable and higher long-term returns has come under scrutiny, including recent data showing long-run underperformance of ESG funds over the past five years. In this Kenan Insight, we provide some clarification based on recent research that revisits fundamental questions: why and how some investors take ESG factors into account in the first place.
With a recent report from the United Nations warning that climate change has already begun to cause irreversible damage, experts during the 2022 Kenan Institute Frontiers of Entrepreneurship Conference discussed the role innovation can – and should – be playing to combat these ill effects. This week’s insight explores the topic through Q&A with Dr. Eric Toone, executive managing director and technology lead at Breakthrough Energy Ventures, and Dr. Jacqueline Pless, the Fred Kayne (1960) Career Development Professor of Entrepreneurship at MIT Sloan School of Management.
The investigations following the attacks of September 11, 2001, showed that our ability to verify a person’s identity is crucial to our national security. As pointed out by The 9/11 Commission Report (National Commission on Terrorists Attacks Upon the United States, 2004), travel documents are as important as weapons for terrorists. To carry out an attack on American soil, foreign terrorists must cross our borders—which requires passing an identification screening. A valid passport also allows a terrorist to obtain other valid documents (e.g., driver’s license, credit cards, health insurance card) that are important to performing normal life activities while maintaining a low profile and avoiding detection. Four projects, currently in different stages of implementation, use Radio Frequency Identification (RFID) or Machine-Readable Zones (MRZ) technologies for verification and validation of identity in the United States. These programs are (1) e-Passport, (2) PASS Card, (3) Real ID, and (4) Enhanced Driver’s License. The use of RFID enables data to be stored electronically in chips embedded in identification documents and shared quickly in digital format by law enforcement personnel. Documents with RFID chips and a secure networking environment to exchange data are deemed more secure and less prone to counterfeiting than conventional, non-electronic documents. However, there is still debate about how to best balance the security benefits from RFID-enabled identification documents with concerns about privacy.